Tau protein accumulation prediction apparatus using machine learning and tau protein accumulation prediction method using the same

Abstract

Disclosed is herein a tau protein accumulation prediction method that includes: a process of inputting: at least one of neuropsychological test information, APOE4 genotype information, positron emission tomography (PET) information, atrophy information of a hippocampal volume, and atrophy information of a cerebral cortical thickness; clinical information; and mild cognitive impairment expression stage information; and a process of calculating a prediction result indicating whether or not a tau protein is accumulated on the brain. According to the tau protein accumulation prediction method, severity or prognosis of a brain disease can be predicted.

What is claimed is: 
     
         1 . A tau protein accumulation prediction method comprising:
 a process of inputting: at least one of neuropsychological test information, APOE4 genotype information, positron emission tomography (PET) information, atrophy information of a hippocampal volume, and atrophy information of a cerebral cortical thickness; clinical information; and mild cognitive impairment expression stage information; and   a process of calculating a prediction result indicating whether or not a tau protein is accumulated on the brain.   
     
     
         2 . The tau protein accumulation prediction method of  claim 1 , wherein the process of calculating a prediction result includes a process of analyzing whether or not a tau protein load is accumulated, using a machine learning algorithm out of classification analysis models. 
     
     
         3 . The tau protein accumulation prediction method of  claim 2 , wherein the machine learning algorithm includes a tree-based model. 
     
     
         4 . The tau protein accumulation prediction method of  claim 3 , wherein the tree-based model includes one of a gradient boosting machine (GBM) model and a random forest (RF) model. 
     
     
         5 . The tau protein accumulation prediction method of  claim 1 , wherein the clinical information includes at least one of an age, a gender, and educated years of a subject. 
     
     
         6 . A tau protein accumulation prediction apparatus comprising:
 an input unit configured to receive: at least one of neuropsychological test information, APOE4 genotype information, positron emission tomography (PET) information, atrophy information of a hippocampal volume, and atrophy information of a cerebral cortical thickness; clinical information; and mild cognitive impairment expression stage information; and   a processor configured to calculate a prediction result indicating whether or not a tau protein is accumulated on the brain.   
     
     
         7 . The tau protein accumulation prediction apparatus of  claim 6 , wherein the processor analyzes whether or not a tau protein load is accumulated, using a machine learning algorithm out of classification analysis models. 
     
     
         8 . The tau protein accumulation prediction apparatus of  claim 7 , wherein the machine learning algorithm includes a tree-based model. 
     
     
         9 . The tau protein accumulation prediction apparatus of  claim 8 , wherein the tree-based model includes one of a gradient boosting machine (GBM) model and a random forest (RF) model. 
     
     
         10 . The tau protein accumulation prediction apparatus of  claim 6 , wherein the clinical information includes at least one of an age, a gender, and educated years of a subject.